Results 31 to 40 of about 701,410 (306)

Convolutional Neural Networks: A Roundup and Benchmark of Their Pooling Layer Variants

Algorithms, 2022
One of the essential layers in most Convolutional Neural Networks (CNNs) is the pooling layer, which is placed right after the convolution layer, effectively downsampling the input and reducing the computational power required.
Nikolaos-Ioannis Galanis, Panagiotis Vafiadis, Kostas-Gkouram Mirzaev, George A. Papakostas   +3 more
doaj   +1 more source

Weakly Supervised U-Net with Limited Upsampling for Sound Event Detection

Applied Sciences, 2023
Sound event detection (SED) is the task of finding the identities of sound events, as well as their onset and offset timings from audio recordings. When complete timing information is not available in the training data, but only the event identities are ...
Sangwon Lee, Hyemi Kim, Gil-Jin Jang
doaj   +1 more source

Contrastive Learning for Action Assessment Using Graph Convolutional Networks With Augmented Virtual Joints

IEEE Access, 2023
A fine-grained detection of posture problems for action assessment has a wide range of applications for health care, sports, and rehabilitation. However, there exist many design challenges, e.g., the difficulty of detecting subtle deviations in actions ...
Chung-In Joung, Seunghwan Byun, Seungjun Baek   +2 more
doaj   +1 more source

Active Surveillance of Asymptomatic, Presymptomatic, and Oligosymptomatic SARS-CoV-2-Infected Individuals in Communities Inhabiting Closed or Semi-closed Institutions

Frontiers in Medicine, 2021
Background: The high COVID-19 dissemination rate demands active surveillance to identify asymptomatic, presymptomatic, and oligosymptomatic (APO) SARS-CoV-2-infected individuals.
Nicolás Ambrosis, Pablo Martin Aispuro, Keila Belhart, Daniela Bottero, Renée Leonor Crisp, María Virginia Dansey, María Virginia Dansey, Magali Gabrielli, Oscar Filevich, Valeria Genoud, Alejandra Giordano, Min Chih Lin, Min Chih Lin, Anibal Lodeiro, Anibal Lodeiro, Felipe Marceca, Felipe Marceca, Nicolás Pregi, Nicolás Pregi, Federico Remes Lenicov, Luciana Rocha-Viegas, Luciana Rocha-Viegas, Erika Rudi, Guillermo Solovey, Guillermo Solovey, Eugenia Zurita, Adali Pecci, Adali Pecci, Roberto Etchenique, Roberto Etchenique, Daniela Hozbor   +30 more
doaj   +1 more source

Recombinator Networks: Learning Coarse-to-Fine Feature Aggregation [PDF]

, 2016
Deep neural networks with alternating convolutional, max-pooling and decimation layers are widely used in state of the art architectures for computer vision.
Honari, Sina, Pal, Christopher, Vincent, Pascal, Yosinski, Jason   +3 more
core   +1 more source

Understanding the Barriers to Pooled SARS-CoV-2 Testing in the United States

Microbiology Spectrum, 2021
Pooled testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection is instrumental for increasing test capacity while decreasing test cost.
Eli P. Fenichel, R. Tobias Koch, Anna Gilbert, Gregg Gonsalves, Anne L. Wyllie   +4 more
doaj   +1 more source

From Spectrum Pooling to Space Pooling: Opportunistic Interference Alignment in MIMO Cognitive Networks [PDF]

, 2009
We describe a non-cooperative interference alignment (IA) technique which allows an opportunistic multiple input multiple output (MIMO) link (secondary) to harmlessly coexist with another MIMO link (primary) in the same frequency band.
Debbah, M., Fawaz, N., Lasaulce, S., Perlaza, S. M.   +3 more
core   +5 more sources

Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting

, 2017
We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requirements.
Fu, Gengshen, Mandal, Arindam, Matsoukas, Spyros, Panchapagesan, Sankaran, Raju, Anirudh, Strom, Nikko, Sun, Ming, Tucker, George, Vitaladevuni, Shiv   +8 more
core   +1 more source

Compact Bilinear Pooling

, 2016
Bilinear models has been shown to achieve impressive performance on a wide range of visual tasks, such as semantic segmentation, fine grained recognition and face recognition.
Beijbom, Oscar, Darrell, Trevor, Gao, Yang, Zhang, Ning   +3 more
core   +1 more source

On the Statistical Multiplexing Gain of Virtual Base Station Pools [PDF]

, 2014
Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing.
Gong, Jie, Liu, Jingchu, Niu, Zhisheng, Xu, Shugong, Zhou, Sheng   +4 more
core   +1 more source